Lipidomic Analysis Reveals Serum Alteration of Plasmalogens in Patients Infected With ZIKA Virus
Bibliographic record
Abstract
family. Since the large outbreaks in French Polynesia in 2013-2014 and in Brazil in 2015, ZIKV has been considered a new public health threat. Similar to other related flavivirus, ZIKV is associated with mild and self-limiting symptoms such as rash, pruritus, prostration, headache, arthralgia, myalgia, conjunctivitis, lower back pain and, when present, a short-term low grade fever. In addition, ZIKV has been implicated in neurological complications such as neonatal microcephaly and Guillain-Barré syndrome in adults. Herein, serum lipidomic analysis was used to identify possible alterations in lipid metabolism triggered by ZIKV infection. Patients who presented virus-like symptoms such as fever, arthralgia, headache, exanthema, myalgia and pruritus were selected as the control group. Our study reveals increased levels of several phosphatidylethanolamine (PE) lipid species in the serum of ZIKV patients, the majority of them plasmenyl-phosphatidylethanolamine (pPE) (or plasmalogens) linked to polyunsaturated fatty acids. Constituting up to 20% of total phospholipids in humans, plasmalogens linked to polyunsaturated fatty acids are particularly enriched in neural membranes of the brain. The biosynthesis of plasmalogens requires functional peroxisomes, which are important sites for viral replication, including ZIKV. Thus, increased levels of plasmalogens in serum of ZIKV infected subjects suggest a link between ZIKV life cycle and peroxisomes. Our data provide important insights into specific host cellular lipids that are likely associated with ZIKV replication and may serve as platform for antiviral strategy against ZIKV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".